120 citations · 532 across the 34 of their papers we have counts for
5 papers · 1 filter
Cardiocirculatory Computational Models for the Study of Hypertension
Simone Celora, Andrea Tonini, Francesco Regazzoni +3
In this work, we develop patient-specific cardiocirculatory models with the aim of building Digital Twins for hypertension. In particular, in our pathophysiology-based framework, w…
Improvements on uncertainty quantification with variational autoencoders
Andrea Tonini, Tan Bui-Thanh, Francesco Regazzoni +2
Inverse problems aim to determine model parameters of a mathematical problem from given observational data. Neural networks can provide an efficient tool to solve these problems. I…
Emergence of Structure in Ensembles of Random Neural Networks
Luca Muscarnera, Luigi Loreti, Giovanni Todeschini +2
Randomness is ubiquitous in many applications across data science and machine learning. Remarkably, systems composed of random components often display emergent global behaviors th…
Influence of cellular mechano-calcium feedback in numerical models of cardiac electromechanics
Irena Radišić, Francesco Regazzoni, Michele Bucelli +3
Multiphysics and multiscale mathematical models enable the non-invasive study of cardiac function. These models often rely on simplifying assumptions that neglect certain biophysic…
Combining physics-based and data-driven models: advancing the frontiers of research with Scientific Machine Learning
Alfio Quarteroni, Paola Gervasio, Francesco Regazzoni
Scientific Machine Learning (SciML) is a recently emerged research field which combines physics-based and data-driven models for the numerical approximation of differential problem…